1. Field of the Invention
The present invention relates to an image processing method, apparatus, and system for determining the human face in an image, and a storage medium.
2. Background of the Invention
Image processing method for detecting or extracting a feature region of a given image is very useful. For example, it can be used to determine the human face(s) in a given image. It is very useful to determine the human faces in an image, especially in an image with a complex background. Such a method can be used in many fields, such as telecommunication conferences, person-to-machine interface, security checking-up, monitor system for tracking human face, and image compression, etc.
It is easy for a human being (an adult or a baby) to identify human face in an image with a complex background. However, no efficient way has been found out to detect human face(s) in an image automatically and quickly.
Determining whether a region or a sub-image in an image contains a human face is an importing step in the human face detection. At present, there are many ways for detecting human face. For example, a human face can be detected by making use of some salient features (such as two eyes, the mouth, the nose,.etc.) and the inherent geometric positional relations among the salient features, or making use of the symmetric characters of human face, complexion features of human face, template matching and neural network method, etc. For instance, a method is described in Haiyuan Wu, “Face Detection and Rotations Estimation using Color Information.”, the 5th IEEE International Workshop on Robot and Human Communication, 1996, pp 341–346, in which a method is, given for utilizing human face features (two eyes and the mouth) and relations among the features to detect human face. In this method, the image region to be determined is first studied to find out whether the needed human face features can be extracted. If yes, then the matching degree of the extracted face human features to a known is human face model investigated, wherein the human face model describes the geometric relations among the human face features. If the matching degree is high, the image region is supposed to be an image of a human face. Otherwise, it is determined that the image region does not contains a human face. However, the method relies too much on the quality of the image to be investigated, and it is too much influenced by, lighting conditions, the complexity of the image's background and the human race difference. Especially, it is very hard to determine human face exactly when the image quality is bad.
There have been other prior art disclosures regarding human face detection, such as:    1. “Region-Based Template Deformation And Masking For Eye-Feature Extraction And. Description”, JYH-YUAN DENG and PEIPEI LAI, Pattern Recognition, Vol. 30, No. 3, pp. 403–419,1997;    2. “Generalized likelihood ratio-based face detection and extraction of mouth features”, C. Kervrann, F. Davoine, P. Perez, R. Forchheimer, C. Labit, Pattern Recognition Letters 18 (1997)899–912;    3. “Face Detection From Color Images Using a Fuzzy Pattern Matching Method”, Haiyuan Wu, Qian Chen, and. Masahiko Yachida, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 21, No 6, June 1999;    4. “Human Face Detection In a Complex Background”, Guangzheng Yang and Thomas S. Huang, Pattern Recognition, Vol. 27, No. 1, pp. 53–63. 1994;    5. “A Fast Approach for Detecting Human faces in a Complex Background”, Kin-Man Lam, Proceedings of the 1998 IEEE International, Symposium on Circuits and System, 1998, ISCAS'98 Vol. 4, pp 85–88.